# Efficient Detection of DDoS Attacks Using a Hybrid Deep Learning Model with Improved Feature Selection

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/efficient-detection-of-ddos-attacks-using-a-hybrid-deep-learning-model-with/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Daniyal Alghazzawi,Omaimah Bamasag,Hayat Ullah,Muhammad Zubair Asghar |
| Citations | 140 |
| DOI | 10.3390/app112411634 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2076-3417/11/24/11634/pdf?version=1640198282 |
| OpenAlex ID | https://openalex.org/W4200206556 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Hayat Ullah](https://scholariq.org/researchers/hayat-ullah/)

## Paper journal

- [Applied Sciences](https://scholariq.org/journals/applied-sciences/)

## Paper primary topic

- [Network Security and Intrusion Detection](https://scholariq.org/topics/network-security-and-intrusion-detection/)

## Paper topics

- [Network Security and Intrusion Detection](https://scholariq.org/topics/network-security-and-intrusion-detection/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)
- [Advanced Malware Detection Techniques](https://scholariq.org/topics/advanced-malware-detection-techniques/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.